Jordi Madrenas

148 total papers · 1.2k total citations
99 papers, 775 citations indexed

About

Jordi Madrenas is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Jordi Madrenas has authored 99 papers receiving a total of 775 indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Electrical and Electronic Engineering, 34 papers in Biomedical Engineering and 25 papers in Artificial Intelligence. Recurrent topics in Jordi Madrenas's work include Advanced Memory and Neural Computing (31 papers), Advanced MEMS and NEMS Technologies (23 papers) and Analog and Mixed-Signal Circuit Design (22 papers). Jordi Madrenas is often cited by papers focused on Advanced Memory and Neural Computing (31 papers), Advanced MEMS and NEMS Technologies (23 papers) and Analog and Mixed-Signal Circuit Design (22 papers). Jordi Madrenas collaborates with scholars based in Spain, Japan and Italy. Jordi Madrenas's co-authors include Daniel Fernández, Eduard Alarcón, C. Reig, Andrea De Marcellis, Susana Cardoso, P. P. Freitas, María‐Dolores Cubells‐Beltrán, Michel Verleysen, Manuel Moreno‐Eguilaz and Joana D. Santos and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Jordi Madrenas

95 papers receiving 744 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Jordi Madrenas	552	242	155	136	117	99	775
Alister Hamilton	484 0.9×	243 1.0×	199 1.3×	37 0.3×	160 1.4×	72	812
Fabio L. Traversa	390 0.7×	87 0.4×	195 1.3×	231 1.7×	88 0.8×	71	706
Yoshihito Amemiya	742 1.3×	277 1.1×	112 0.7×	231 1.7×	71 0.6×	108	896
Philippe O. Pouliquen	511 0.9×	307 1.3×	163 1.1×	34 0.3×	114 1.0×	65	782
Sina Balkır	577 1.0×	180 0.7×	127 0.8×	37 0.3×	32 0.3×	81	895
A. P. Thakoor	464 0.8×	65 0.3×	288 1.9×	140 1.0×	38 0.3×	67	830
Ahmed Lakhssassi	228 0.4×	145 0.6×	37 0.2×	183 1.3×	50 0.4×	134	860
Seungchul Jung	654 1.2×	133 0.5×	104 0.7×	105 0.8×	39 0.3×	37	729
Euripidis Glavas	198 0.4×	60 0.2×	166 1.1×	91 0.7×	215 1.8×	66	813
Krishna Lal Baishnab	358 0.6×	211 0.9×	145 0.9×	41 0.3×	17 0.1×	90	664

Countries citing papers authored by Jordi Madrenas

Since Specialization

Citations

This map shows the geographic impact of Jordi Madrenas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jordi Madrenas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordi Madrenas more than expected).

Fields of papers citing papers by Jordi Madrenas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jordi Madrenas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jordi Madrenas. The network helps show where Jordi Madrenas may publish in the future.

Co-authorship network of co-authors of Jordi Madrenas

This figure shows the co-authorship network connecting the top 25 collaborators of Jordi Madrenas. A scholar is included among the top collaborators of Jordi Madrenas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jordi Madrenas. Jordi Madrenas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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